• 제목/요약/키워드: automatic identification

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Study on Analysis and Improvement of Management System Standard Software for Aids to Navigation (항로표지 관리운영시스템 표준소프트웨어 문제점 분석 및 개선방안 연구)

  • Hyeong-Woo Lee;Dong-Hyeon Heo;A-Ro Nam
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 한국항해항만학회 2022년도 추계학술대회
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    • pp.36-37
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    • 2022
  • 선박의 안천한 항해를 돕기 위하여 해상에 항로표지를 설치하여 운영하고 있다. 해상 ICT(Information and Communications Technology)의 발달로 AtoN AIS(Automatic Identification System) 및 CDMA(Code Division Multiple Access), LTE(Long Term Evolution) 등 다중통신망을 이용하여 항로표지의 상태를 감시하고 제어가 가능해짐에 따라 해양수산부에서는 항로표지 관리운영시스템을 운영하고 있다. e-Navigation 및 자율운항선박 분야 등에 항로표지 스마트화를 위해 정확한 항로표지 정보가 요구된다. 본 논문에서는 정확한 항로표지 정보 제공을 위해 관리운영시스템 표준소프트웨어 문제점을 분석하고 개선방안에 대해서 소개한다.

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AIS 항적 데이터 기반 선박의 충돌 위험 영역 예측에 관한 기초 연구

  • 박정홍;최진우;김혜진
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 한국항해항만학회 2021년도 추계학술대회
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    • pp.181-182
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    • 2021
  • 본 연구에서는 자율운항선박의 원격 관제 및 제어하는 과정에서 원격 운항자에게 사전 충돌 위험 정보를 제공하기 위해 선박자동식별시스템(AIS, Automatic Identification System)의 항적 정보를 토대로 자율운항선박의 운항 경로 상에 잠재된 충돌 위험 영역을 예측하기 위한 기초 연구를 수행하였다. 자율운항선박의 운항 경로 상에 근접한 타선의 AIS 정보에는 기본적으로 선박의 위치, 속도, 침로에 대한 정보가 반영되어 있으므로, 이러한 정보를 토대로 일정 시간 동안 운항 경로를 예측할 수 있다. 그리고 예측한 정보를 기반으로 대표적 충돌 위험 지수인 최근접점(CPA, Closest Point of Approach)과 최근접점 거리(DCPA, Distance to CPA) 정보를 활용하여 충돌 위험 영역을 2차원 공간상에서 예측하였다. 제안된 방법은 실제 AIS 항적 데이터를 활용한 수치 시뮬레이션을 수행하여 초기 결과를 검증하였다.

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Algorithm Implementation for Detection and Tracking of Ships Using FMCW Radar (FMCW Radar를 이용한 선박 탐지 및 추적 기법 구현)

  • Hong, Dan-Bee;Yang, Chan-Su
    • Journal of the Korean Society for Marine Environment & Energy
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    • 제16권1호
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    • pp.1-8
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    • 2013
  • This study focuses on a ship detection and tracking method using Frequency Modulated Continuous Wave (FMCW) radar used for horizontal surveillance. In general, FMCW radar can play an important role in maritime surveillance, because it has many advantages such as low warm-up time, low power consumption, and its all weather performance. In this paper, we introduce an effective method for data and signal processing of ship's detecting and tracking using the X-band radar. Ships information was extracted using an image-based processing method such as the land masking and morphological filtering with a threshold for a cycle data merged from raw data (spoke data). After that, ships was tracked using search-window that is ship's expected rectangle area in the next frame considering expected maximum speed (19 kts) and interval time (5 sec). By using this method, the tracking results for most of the moving object tracking was successful and those results were compared with AIS (Automatic Identification System) for ships position. Therefore, it can be said that the practical application of this detection and tracking method using FMCW radar improve the maritime safety as well as expand the surveillance coverage cost-effectively. Algorithm improvements are required for an enhancement of small ship detection and tracking technique in the future.

Design and Implementation of AR Model based Automatic Identification and Restoration Scheme for Line Scratches in Old Films (AR 모델 기반의 고전영화의 긁힘 손상의 자동 탐지 및 복원 시스템 설계와 구현)

  • Han, Ngoc-Soc;Kim, Seong-Whan
    • The KIPS Transactions:PartB
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    • 제17B권1호
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    • pp.47-54
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    • 2010
  • Old archived film shows two major defects: line scratch and blobs. In this paper, we present a design and implementation of an automatic video restoration system for line scratches observed in archived film. We use autoregressive (AR) image model because we can make stochastic and specifically autoregressive image generation process with our PAST-PRESENT model and Sampling Pattern. We designed locality maximizing scanning pattern, which can generate nearly stationary time-like series of pixels, which is a strong requirement for a stochastic series to be autoregressive. The sampled pixel series undergoes filtering and model fitting using Durbin-Levinson algorithm before interpolation process. We designed three-stage film restoration system, which includes (1) film acquisition from VHS tapes, (2) simple line scratch detection and restoration, and (3) manual blob identification and sophisticated inpainting scheme. We implemented film acquisition and simple inpainting scheme on Texas Instruments DSP board TMS320DM642 EVM, and implemented our AR inpainting scheme on PC for sophisticated restoration. We experimented our scheme with two old Korean films: "Viva Freedom" and "Robot Tae-Kwon-V", and the experimental results show that our scheme improves Bertalmio's scheme for subjective quality (MOS), objective quality (PSNR), and especially restoration ratio (RR), which reflects how much similar to the manual inpainting results.

Classification of Passing Vessels Around the Ieodo Ocean Research Station Using Automatic Identification System (AIS): November 21-30, 2013 (선박자동식별장치(AIS)를 이용한 이어도 종합해양과학기지 주변 통항 선박의 분류: 2013년 11월 21일~30일)

  • Hong, Dan-Bee;Yang, Chan-Su
    • Journal of the Korean Society for Marine Environment & Energy
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    • 제17권4호
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    • pp.297-305
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    • 2014
  • In this study, we installed the Automatic Identification System (AIS) receiver on the Ieodo Ocean Research Station (IORS) from November 21 to 30, 2013 in order to monitor marine traffic and fishery activity in the jurisdictional sea area. The collected AIS raw data consist of static data report (MMSI, IMO NO., Call Sign, Ship Name, etc.) and position information report (position, speed, course, etc.), and the developed program was applied to classify ships according to ship flag and type information. The nationalities are released from the first three-digit numbers (MID) of MMSI, but in general most of small ships do not send an exact ship flag through Class B type AIS, a simplified and low-power equipment. From AIS data with flag information, ships under the flag of China had the highest frequency and the second was Korean flag, while in ship type cargo and fishing vessels were dominant in sequence. As for the ships without flag information, we compared the tracks with others in order to estimate ship flags. It can be said that fleets of ships with Chinese frequently appear sail together for fisheries over the waters, because the unknown ships followed a similar moving pattern with Chinese fishing vessels.

A Study on High-Speed Extraction of Bar Code Region for Parcel Automatic Identification (소포 자동식별을 위한 바코드 관심영역 고속 추출에 관한 연구)

  • Park, Moon-Sung;Kim, Jin-Suk;Kim, Hye-Kyu;Jung, Hoe-Kyung
    • The KIPS Transactions:PartD
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    • 제9D권5호
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    • pp.915-924
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    • 2002
  • Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60~80msec, and the accuracy has been accomplished over 99.44 percentage.

An Algorithm for Filtering False Minutiae in Fingerprint Recognition and its Performance Evaluation (지문의 의사 특징점 제거 알고리즘 및 성능 분석)

  • Yang, Ji-Seong;An, Do-Seong;Kim, Hak-Il
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • 제37권3호
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    • pp.12-26
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    • 2000
  • In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

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Ship Detection Based on KOMPSAT-5 SLC Image and AIS Data (KOMPSAT-5 SLC 영상과 AIS 데이터에 기반한 선박탐지)

  • Kim, Donghan;Lee, Yoon-Kyung;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • 제36권2_2호
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    • pp.365-377
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    • 2020
  • Continuous monitoring and immediate response is essential to protect the national maritime territory and maritime resources from the activities of illegal ships. Synthetic Aperture Radar (SAR) images with a wide range of images are effective for maritime surveillance asthe weather and day-night conditions rarely affect to image acquisition. However, an effective ship detection is not easy due to the huge data size of SAR images and various characteristics such as the speckle noise. In this study, the Human Visual Attention System (HVAS) algorithm was applied to KOMPSAT-5 to extract the initial targets, and the SAR-Split algorithm depending on the imaging modes was used to remove false alarms. The detected targets were finally selected by the Constant False Alarm Rate (CFAR) algorithm and matched with the ship's Automatic Identification System (AIS) information. Overall, the detected targets were well matched with AIS data, but some false alarms by ship wakes were observed. The detection rate was about 80% in ES mode and about 64% in ST mode. It is expected that the developed ship detection algorithm will contribute to the construction of a wide area maritime surveillance network.

Design of Automatic Classification System of Black Plastics Based on Support Vector Machine Using Raman Spectroscopy (라만분광법을 이용한 SVM 기반 흑색 플라스틱 자동 분류 시스템의 설계)

  • Bae, Jong-Soo;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • 제26권5호
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    • pp.416-422
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    • 2016
  • Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

Operational Ship Monitoring Based on Integrated Analysis of KOMPSAT-5 SAR and AIS Data (Kompsat-5 SAR와 AIS 자료 통합분석 기반 운영레벨 선박탐지 모니터링)

  • Kim, Sang-wan;Kim, Dong-Han;Lee, Yoon-Kyung
    • Korean Journal of Remote Sensing
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    • 제34권2_2호
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    • pp.327-338
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    • 2018
  • The possibility of ship detection monitoring at operational level using KOMPSAT-5 Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) data is investigated. For the analysis, the KOMPSAT-5 SLC images, which are collected from the west coast of Shinjin port and the northern coast of Jeju port are used along with portable AIS data from near the coast. The ship detection algorithm based on HVAS (Human Visual Attention System) was applied, which has significant advantages in terms of detection speed and accuracy compared to the commonly used CFAR (Constant False Alarm Rate). As a result of the integrated analysis, the ship detection from KOMPSAT-5 and AIS were generally consistent except for small vessels. Some ships detected in KOMPSAT-5 but not in AIS are due to the data absence from AIS, while it is clearly visible in KOMPSAT-5. Meanwhile, SAR imagery also has some false alarms due to ship wakes, ghost effect, and DEM error (or satellite orbit error) during object masking in land. Improving the developed ship detection algorithm and collecting reliable AIS data will contribute for building wide integrated surveillance system of marine territory at operational level.